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Design a Conversational AI Assistant

Last updated: Apr 6, 2026

Quick Overview

This question evaluates system design, distributed systems, and real-time inference-serving competencies for building large-scale conversational AI products within the System Design category.

  • medium
  • OpenAI
  • System Design
  • Software Engineer

Design a Conversational AI Assistant

Company: OpenAI

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Technical Screen

Design a large-scale conversational AI product similar to ChatGPT. Users should be able to: - start a new conversation, - send prompts, - receive streaming responses, - continue multi-turn conversations, - view chat history, - regenerate an answer, - optionally give feedback on responses. The system should support millions of users, low-latency response streaming, high availability, abuse prevention, and safe content handling. Focus on the online serving architecture rather than training a foundation model from scratch. Discuss: - functional and non-functional requirements, - APIs and core data model, - high-level architecture, - conversation memory and context-window management, - model routing and inference serving, - scaling, reliability, and cost control, - security, privacy, and moderation.

Quick Answer: This question evaluates system design, distributed systems, and real-time inference-serving competencies for building large-scale conversational AI products within the System Design category.

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OpenAI
Jan 29, 2026, 12:00 AM
Software Engineer
Technical Screen
System Design
18
0
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Design a large-scale conversational AI product similar to ChatGPT.

Users should be able to:

  • start a new conversation,
  • send prompts,
  • receive streaming responses,
  • continue multi-turn conversations,
  • view chat history,
  • regenerate an answer,
  • optionally give feedback on responses.

The system should support millions of users, low-latency response streaming, high availability, abuse prevention, and safe content handling. Focus on the online serving architecture rather than training a foundation model from scratch.

Discuss:

  • functional and non-functional requirements,
  • APIs and core data model,
  • high-level architecture,
  • conversation memory and context-window management,
  • model routing and inference serving,
  • scaling, reliability, and cost control,
  • security, privacy, and moderation.

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